以密閉式藻類毒性試驗研究前親電性及親電性物質之定量結構活性關係

Abstract

藻類在水體食物鏈中處於初級生產者之位置，在水體生態影響評估中佔重要之地位，根據OECD化學物風險管理之架構(REACH Program)，環境危害評估主要以魚類、水蚤、及藻類三種生態食物鍊上不同階層之生物進行評估，且對數據不足之化學物准許以定量結構活性關係（QSAR, Quantitative Structure－activity Relationships）推估其毒性，故高品質之毒性數據資料庫及建立可靠的QSAR關係對化學物風險管理而言，兩者皆具必要性。 α,β-不飽和化合物為工業廣泛使用之揮發性有機物，其毒性作用機制為親電性及前親電性，於反應性物質中為一種重要機制，目前已有其對魚、纖毛蟲及老鼠肝細胞之定量結構活性關係（QSAR, Quantitative Structure－activity Relationships），親電性參數及空間參數皆與其毒性有關，在現今之毒性數據資料庫中，藻類毒性數據及QSAR關係皆極為不足。 本計畫預計以三年時間，探討α,β-不飽和化合物之毒性作用機制，及結構與毒性之間之關係，並建立適當之QSAR模式，第一年研究之化合物為前親電性之α,β-不飽和醇，第二、三年分別研究α,β-不飽和酯（丙烯酸酯及甲基丙烯酸酯）及α,β-不飽和酮。目的為填補高品質藻類毒性數據資料庫之不足及建立預測此類毒性物質毒性之QSAR關係。

As the primary producer in the aquatic food chain, algae play an important role in the effects assessment of aquatic system. According to the REACH program in the European Union, organisms of three different trophic levels, i.e., fish, daphnia and algae, are used for environmental hazard assessment. Furthermore, OECD allows utilizing QSAR (Quantitative Structure－activity Relationships) to estimate toxicity for data-scarced chemicals. Therefore, high-quality toxicity dataset and reliable QSARs are essential for chemical risk management. α,β-unsaturated compounds are the prevalent industrial organic chemicals in industries. These compounds exhibit an electrophilic or a proelectrophilic mechanism of toxic action, which are a important class of reactive toxicants. Currently, toxicity data and QSARs for fish, ciliate and rat hepatocyte are available in exsisting database. However, the toxic effects and QSARs for this category of compounds in relation to algae are extremely deficient. This project attempts to investigate the mechanism of toxic action, the relationships between structures and toxicity of α,β-unsaturated compounds, and to develop appropriate QSAR models. Compounds to be investigated are: proelectrophilic α,β-unsaturated alchohols (first year), electrophilic α,β-unsaturated easters (second year) and α,β-unsaturated ketones (third year). The purpose of this study is to fill the high quality algal toxicity dataset, and to develop the QSARs for these kinds of compounds.